The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
We consider the use of Bayesian topic models in the analysis of computer network traffic. Our approach utilizes latent Dirichlet allocation and time-varying dynamic latent Dirich...
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
—In a sensor network, an important problem is to provide privacy to the event detecting sensor node and integrity to the data gathered by the node. Compromised source privacy can...
Communication between humans is rich in complexity and is not limited to verbal signals; emotions are conveyed with gesture, pose and facial expression. Facial Emotion Recognition ...